By Shaun Hurst, Principal Regulatory Adviser at Smarsh
As financial services continues to face an ever changing and increasingly complex regulatory environment, the industry must harness new tools and technologies to meet the challenge. With AI’s potential to revolutionise risk management and surveillance, it is time to embrace the future and integrate AI into compliance systems.
By now, we can all agree that the introduction of AI into the public realm is not merely a fleeting trend, but a substantial shift that is here to stay. From the way we communicate and consume media to the manner in which we travel and manage our homes, AI is at the forefront of innovation, streamlining operations and fostering new ways of working. The AI revolution is not just imminent; it is already well underway, redefining our daily lives.
Financial services, among other sectors, stand on the cusp of this revolution. Coinciding with these technological advances that are setting a new standard of working, the sector is also increasingly being held under the microscope by regulators too, with the FCA launching multiple probes earlier this year into top city firms.
Unsurprisingly, the AI revolution is one that promises to redefine the landscape of risk management and ethical governance as well, with the potential to significantly support firms in these areas. However, the path to full integration is strewn with challenges that must be navigated with care and foresight.
The challenges and ethical considerations
The practical challenges of implementing AI into regulatory compliance are numerous. Integrating this advanced technology into legacy systems presents a significant hurdle, often requiring substantial investment and a strategic overhaul of existing infrastructures.
The concerns surrounding data privacy are important too, as the handling of sensitive information must be approached with the utmost caution to maintain client trust and adhere to stringent data protection regulations.
It’s also well known that ethical implications loom over the deployment of AI. There is a palpable fear of job displacement in the compliance industry, although it is more likely that AI will transform job roles rather than render them obsolete. Moreover, the transparency of AI decision-making processes – or the lack thereof – poses a concern. Financial services companies are grappling with the need to demystify the ‘black box’ nature of AI, ensuring that the rationale behind automated decisions is both comprehensible and justifiable.
However, by looking to other industries for learnings and guidance, the healthcare space has clear example of AI’s transformative nature. AI has the potential to empower surgeons to detect anomalies in X-rays with a level of precision that was once the exclusive domain of the most skilled practitioners. Yet, with such advancements come
cautionary tales. The reliance on AI must not breed complacency. There is a danger that professionals might overlook critical details not flagged by the AI, say where a machine directs a doctor’s attention to three points on an X-ray, potentially missing a fourth, crucial anomaly. This highlights the indispensable need for human oversight and the careful balance between technological assistance and professional judgement.
When applying this to communications compliance in financial services, for example, AI could identify a series of suspicious activity in an employees’ channels, but these could all be false alarms. It would take a seasoned compliance professional to spot the message which indicated an actual example of misconduct. Therefore, AI should enhance human expertise, rather than replacing it, in this realm too.
Embracing AI for a robust compliance framework
Despite these challenges, the future of AI in financial services compliance is undeniably firm. AI’s capacity to broaden the regulatory-required surveillance of employees and enhance risk management is particularly promising. Traditional rule-based detection systems, plagued by false positives and inefficiencies, are giving way to more sophisticated AI models that can sift through vast quantities of unstructured data with greater precision. For example, with AI, organisations are presented with the opportunity to streamline their customer due diligence processes, saving time and resources while still effectively identifying their own risks.
Yet, the cost-benefit considerations of investing in AI are complex. Financial services companies must judiciously evaluate the array of AI solutions on offer, weighing the upfront costs against the long-term benefits of enhanced compliance, operational efficiency and avoidance of reputational and financial damage of fines. The pace at which AI technology evolves necessitates a commitment to continuous learning and adaptation, ensuring that compliance systems remain at the cutting edge. What’s more, it is vital that AI is developed and used responsibly to ensure its ethical use and to build trust and ensure fairness in its decision-making process
The successful implementation of AI in regulatory systems is not about replacing people or existing technology; it is about leveraging AI where needed to assist and amplify human capabilities and complementing existing expertise. AI can facilitate more investigative and analytical approaches to compliance, enabling professionals to delve deeper into the nuances of regulatory practices. As financial services companies expand their horizons, embracing AI becomes not just a strategic move but a necessity to navigate the complex regulatory environment effectively. Its implementation can shift compliance from a reactive to proactive approach, helping to identify potential issues before they escalate to major problems.
In embracing AI, financial services companies must commit to a future where compliance is not only more robust, but also more intelligent and responsive. The integration of AI into compliance systems is an opportunity to redefine the standards of regulatory excellence, ensuring that the financial sector remains both innovative and trustworthy.
